General Classification
3931 papers with code • 11 benchmarks • 8 datasets
Algorithms trying to solve the general task of classification.
Benchmarks
These leaderboards are used to track progress in General Classification
Libraries
Use these libraries to find General Classification models and implementations
MNIST
Fashion-MNIST
Adult
iris
Hyper-Kvasir Dataset
Wine
Kvasir-Capsule
CVR
Latest papers
SVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained Models
To combat this, a series of light-weight adaptation methods have been proposed to efficiently adapt such models when limited supervision is available.
Explainable Abuse Detection as Intent Classification and Slot Filling
ago3/plead
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To proactively offer social media users a safe online experience, there is a need for systems that can detect harmful posts and promptly alert platform moderators.
A kernel-based quantum random forest for improved classification
maiyuren/quantum-random-forest
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The emergence of Quantum Machine Learning (QML) to enhance traditional classical learning methods has seen various limitations to its realisation.
Learning Temporal Resolution in Spectrogram for Audio Classification
The audio spectrogram is a time-frequency representation that has been widely used for audio classification.
Domain Adaptation for Question Answering via Question Classification
yueeeeeeee/self-supervised-qa
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COLING 2022
In this work, we investigate the potential benefits of question classification for QA domain adaptation.
Supervised Dimensionality Reduction and Image Classification Utilizing Convolutional Autoencoders
johnnellas/csae
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It turned out that this methodology can also be greatly beneficial in enforcing explainability of deep learning architectures.
Semi-supervised classification using a supervised autoencoder for biomedical applications
cypriengille/semi-supervised-autoencoder
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Experiments show that the SSAE outperforms Label Propagation and Spreading and the Fully Connected Neural Network both on a synthetic dataset and on two real-world biological datasets.
Stop&Hop: Early Classification of Irregular Time Series
We bridge this gap and study early classification of irregular time series, a new setting for early classifiers that opens doors to more real-world problems.
Autism spectrum disorder classification based on interpersonal neural synchrony: Can classification be improved by dyadic neural biomarkers using unsupervised graph representation learning?
One approach might be to rethink how we operationalize the theoretical basis of this disease in machine learning models.
Towards Interpretable Sleep Stage Classification Using Cross-Modal Transformers
jathurshan0330/cross-modal-transformer
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Here, we propose a cross-modal transformer, which is a transformer-based method for sleep stage classification.
